18 citations · 19 across the 6 of their papers we have counts for
6 papers · 1 filter
Automated Re-Identification of Holstein-Friesian Cattle in Dense Crowds
Phoenix Yu, Tilo Burghardt, Andrew W Dowsey +1
Holstein-Friesian detection and re-identification (Re-ID) methods capture individuals well when targets are spatially separate. However, existing approaches, including YOLO-based s…
Self-Supervised Animal Identification for Long Videos
Xuyang Fang, Sion Hannuna, Edwin Simpson +1
Identifying individual animals in long-duration videos is essential for behavioral ecology, wildlife monitoring, and livestock management. Traditional methods require extensive man…
Cattle-CLIP: A Multimodal Framework for Dairy Cattle Behaviour Recognition from Video
Huimin Liu, Jing Gao, Daria Baran +4
Monitoring cattle behaviour provides valuable insights into animal health, productivity and welfare. However, robust behaviour recognition in real-world farm environments remains c…
8-Calves Image dataset
Xuyang Fang, Sion Hannuna, Neill Campbell +1
Automated livestock monitoring is crucial for precision farming, but robust computer vision models are hindered by a lack of datasets reflecting real-world group challenges. We int…
Holstein-Friesian Re-Identification using Multiple Cameras and Self-Supervision on a Working Farm
Phoenix Yu, Tilo Burghardt, Andrew W Dowsey +1
We present MultiCamCows2024, a farm-scale image dataset filmed across multiple cameras for the biometric identification of individual Holstein-Friesian cattle exploiting their uniq…
Universal Bovine Identification via Depth Data and Deep Metric Learning
Asheesh Sharma, Lucy Randewich, William Andrew +7
This paper proposes and evaluates, for the first time, a top-down (dorsal view), depth-only deep learning system for accurately identifying individual cattle and provides associate…